The present invention relates to data analysis tools provided to a user of a business application. More specifically, the present invention relates to the identification and user-utilization of navigation paths between related data elements.
When designing software applications involving business transactions, application developers conventionally use a model-driven architecture and focus on domain specific knowledge. The model driven architectures often include business objects (or business entities) involved in underlying business transactions, such as business entities corresponding to customers, orders and products. These entities are modeled as objects following the paradigm of object orientation.
Each object encapsulates data and behavior of the business entity. For example, a Customer object contains data such as name, address and other personal information for a customer. The Customer object also contains programming code, for example, to create a new Customer, modify the data of an existing Customer and/or save the Customer to a database.
The object model also enables a description of relationships among modeled business entities. For example, a number of Order objects can be associated with a Customer object representing the customer who makes those orders. This is known as an association relationship. Other types of relationships can also be defined, such as compositions. An Order, for example, can be “composed of” a collection of OrderLines. These OrderLines typically do not exist independently of the Order they belong to.
Application developers apply the business logic associated with the object-relational model to their applications. Data that corresponds to objects in the object-relational model is typically stored in a database. Data is commonly retrieved from the relational database utilizing on-line transaction processing (OLTP).
Business applications designed to operate in association with the described model-driven architecture are often linked to a considerable amount of data. The quantity of data can be overwhelming to a user of such applications such that the user has difficulty in deriving or extracting useful information. The relationships that connect various data sets are not necessarily obvious to a user, and are therefor susceptible to being lost analytical and organizational opportunities.